GEM: a generic ecological model for estuaries and coastal waters

Abstract

The set-up, application and validation of a generic ecological model (GEM) for estuaries and coastal waters is presented. This model is a comprehensive ecological model of the bottom of the foodweb, consisting of a set of modules, representing specific water quality processes and primary production that can be combined with any transport model to create a dedicated model for a specific ecosystem. GEM links different physical, chemical and ecological model components into one generic and flexible modelling tool that allows for variable sized, curvilinear grids to accomodate both the requirements for local accuracy while maintaining a relatively short model run-time. The GEM model describes the behaviour of nutrients, organic matter and primary producers in estuaries and coastal waters, incorporating dynamic process modules for dissolved oxygen, nutrients and phytoplankton. GEM integrates the best aspects of existing Dutch estuarine models that were mostly dedicated to only one type of ecosystem, geographic area or subset of processes. Particular strengths of GEM include its generic applicability and the integration and interaction of biological, chemical and physical processes into one predictive tool. The model offers flexibility in choosing which processes to include, and the ability to integrate results from different processes modelled simultaneously with different temporal resolutions. The generic applicability of the model is illustrated using a number of representative examples from case studies in which the GEM model was successfully applied. Validation of these examples was carried out using the 'cost function' to compare model results with field observations. The validation results demonstrated consistent accuracy of the GEM model for various key parameters in both spatial dimensions (horizontally and vertically) as well as temporal dimensions (seasonally and across years) for a variety of water systems without the need for major reparameterisation.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

“…(c) Annual mean SST of satellite data used for simulation of SST-dependent physiological parameters (SST-dependent case). wards and Brindley, 1996;Lancelot et al, 2000;Yamanaka et al, 2004;Blauw et al, 2009). Coupling LTL marine ecosystem models to ocean general circulation models (OGCMs) and Earth system models enables three-dimensional (3-D) quantitative descriptions of the ecosystem and its temporally fine variability (e.g.…”

Assessing Potential Algal Blooms in a Shallow Fluvial Lake by Combining Hydrodynamic Modelling and Remote-Sensed Images

“…The full coupling between ecological and hydrodynamic models, with a large number of equations and calibration parameters for the ecological part e.g., [27,28], is an advancing field in limnology, leading to physically-based interpretations, replacing black-box approaches [29]. The use of coupled ecological and hydrodynamic models is justifiable over long time scales (e.g., seasonal and multi-annual) and very large spatial scales (e.g., very large lakes and sea areas) [30].…”

Hydrodynamic and water quality 3D modelling of the Nam Theun 2 Reservoir (Lao PDR): predictions and results of scenarios related to reservoir management, hydrometeorology and nutrient input

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“…Phytoplankton is simulated with BLOOM (Los & Wijsman., 2007;Blauw et al, 2009;Los, 2009;Smits & van Beek, 2013). In BLOOM the algae species compete within the constraints for available nutrients (N,P,Si), available light (energy), the maximum growth rate and the maximum mortality rate (both temperature functions).…”